The fetch_notion_pages function now includes error handling for
rate-limited searches. If a rate-limited response is received, the
function waits for 10 seconds before retrying the search. This ensures
that the function can handle rate limits and continue fetching Notion
pages.
Co-authored-by: StanGirard <stan@example.com>
Co-authored-by: ZeWed <zewed@example.com>
This commit removes the syncNotion function from the ConnectionCards
component. The function is no longer needed, simplifying the code and
improving maintainability.
# Description
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## Screenshots (if appropriate):
The syncNotion function is no longer needed in the ConnectionCards
component, so it has been removed. This change simplifies the code and
improves maintainability.
# Description
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# Description
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## Screenshots (if appropriate):
The SyncsUser model in sync_models.py now has an optional status field.
This change allows for more flexibility in managing user synchronization
status.
# Description
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# Description
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# Description
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# Description
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## Screenshots (if appropriate):
Closes CORE-207
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# Description
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# Description
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## Screenshots (if appropriate):
# Description
Major PR which, among other things, introduces the possibility of easily
customizing the retrieval workflows. Workflows are based on LangGraph,
and can be customized using a [yaml configuration
file](core/tests/test_llm_endpoint.py), and adding the implementation of
the nodes logic into
[quivr_rag_langgraph.py](1a0c98437a/backend/core/quivr_core/quivr_rag_langgraph.py)
This is a first, simple implementation that will significantly evolve in
the coming weeks to enable more complex workflows (for instance, with
conditional nodes). We also plan to adopt a similar approach for the
ingestion part, i.e. to enable user to easily customize the ingestion
pipeline.
Closes CORE-195, CORE-203, CORE-204
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# Description
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## Screenshots (if appropriate):
# Description
Fix multiple notion bugs 👍
-> Delete your notion sync and all the notion files from the db
-> Ensure a sync is not already running before launching a sync.
-> Add a status to subscribe to for user_sync
---------
Co-authored-by: Antoine Dewez <44063631+Zewed@users.noreply.github.com>
Co-authored-by: Stan Girard <stan@quivr.app>
Co-authored-by: aminediro <aminedirhoussi1@gmail.com>
Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
The commit updates the message content in the `main.py` file of the
chatbot example.
# Description
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# Description
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# Description
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## Screenshots (if appropriate):
# Description
closes#3056.
closes#3198
- Create knowledge route
- Get knowledge route
- List knowledge route : accepts knowledge_id | None. None to list root
knowledge for use
- Update (patch) knowledge to rename and move knowledge
- Remove knowledge: Cascade if parent_id in knowledge and cleanup
storage
- Link storage upload to knowledge_service
- Relax sha1 file constraint
- Tests to all repository / service
---------
Co-authored-by: Stan Girard <girard.stanislas@gmail.com>
# Description
- Save and load brain to disk:
```python
async def main():
with tempfile.NamedTemporaryFile(mode="w", suffix=".txt") as temp_file:
temp_file.write("Gold is a liquid of blue-like colour.")
temp_file.flush()
brain = await Brain.afrom_files(name="test_brain", file_paths=[temp_file.name])
save_path = await brain.save("/home/amine/.local/quivr")
brain_loaded = Brain.load(save_path)
brain_loaded.print_info()
```
# TODO:
- Loading all chat history
- Loading from other vector stores, PG for example can be great ...
# Description
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## Screenshots (if appropriate):
The code changes in `dependencies.py` add support for Azure OpenAI
embeddings by parsing the provided URL and extracting the deployment
name, endpoint, and API version. This allows the application to use
Azure OpenAI embeddings for language processing.
Note: The recent user commits and repository commits are not directly
related to the code changes in `dependencies.py` and are not considered
for the commit message.
# Description
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## Screenshots (if appropriate):